MDT的被试类别与项目选择决断

MDT是对被试进行分类决断的测量理论,在真实的测验情境中具有广泛的适应性。该文首先介绍了MDT的模型结构,然后以一个3个项目的测验演示了该模型中被试类别与项目选择的一系列决断准则,并展望了该理论在我国心理与教育测量中的应用前景。     

职业选择与价值实现

:文章从个体基本要素及价值取向两方面构造了选择职业的数学模型 ,考虑个体效益和社会效益统一的前提下 ,给出确定最优职业的方法 ,并用摸拟数据及模型予以演示     

新生代农民工职业转换的影响因素分析——基于陕西省的调查数据

职业转换率是衡量职业流动的主要指标,也是考察社会阶层流动性和社会公平性的重要指标。以陕西省的实地调查数据为基础,运用交叉列联表和Logistic回归方法分析性别、年龄、户籍所在地、受教育程度、职业技能培训等因素对新生代农民工职业流动的影响。研究发现,性别、年龄、户籍所在地等个人因素对职业转换率没有显著影响,而受教育程度和是否接受职业技能培训等人力资本因素对职业转换率有显著的影响。在此基础上,提出增加新生代农民工职业技术教育培训机会的政策建议。     

不同导向组织文化对员工职业成长的影响研究——基于多群组结构方程的统计分析

以组织文化为自变量,员工职业成长为因变量,构建结构方程模型探究不同导向功能的组织文化对员工职业成长的影响作用,同时探究不同群体间(企业性质、性别、年龄段)的影响差异。实证研究表明:结果导向文化对职业成长显著负相关,员工导向文化对职业成长显著正相关;在员工导向文化对职业成长的影响中,年龄、性别及企业性质未体现显著差异;但在结果导向文化中均体现出明显差异,女性比男性影响显著,老员工对晋升速度具有更强烈的期待与要求,国企员工更倾向于利用职业能力发展来提高晋升速度,民企员工更倾向于利用职业能力发展来提高报酬增长;不同导向功能的组织文化对新生代员工更加敏感。     

基于潜类别随机前沿的区域创新效率及其影响因素分析

运用可根据研究对象的潜在属性内生分组的潜类别随机前沿模型,采用1999-2012年中国各省区数据,研究各省区的创新效率及影响因素。结果表明:以人力资本水平和基础设施状况为条件变量,将全国各省区分成两个技术类别,分别有各自的技术前沿和函数形式,A类别中上海市的创新效率最高,B类别中河北省的创新效率最高;平均来看,各类的创新效率均呈上升趋势,贸易开放、产业结构和金融发展对创新效率均有显著的正向作用,同时创新效率在各类内部均存在俱乐部收敛。     

农民工职业流动的意愿及其影响因素研究——以杭州市建筑业为例

从个体微观的角度对杭州市建筑业农民工的工作情况进行实地调研,具体考察农民工的个人基本特征、家庭特征、工作特征及地区选择特征四类情况,并利用交叉分析和二元逻辑回归模型检验四类特征对农民工职业流动意愿的影响.研究结果显示,地区选择、从业时间、随同的家庭成员人数、工作中的人际关系等因素对农民工选择继续留在建筑业中工作具有显著正向作用.企业和政府等可以通过为农民工在城市创造稳定的生活和就业环境,推进农民工向城市迁移的进程,或可以加强对农民工的就业指导等多种途径来促使农民工维持稳定的职业,从而一定程度上缓解行业中“用工荒”难题.     

层次分析法在职业选择上的运用

文章依据择业排序难以精确定量的事实,选择层次分析法构建了一个职业选择排序模型,通过实用表明该模型可以为职业选择提供半定量分析基础上的科学指导.     

一种新的类别型数据聚类算法

文章基于类别数据集合引入质量和特征向量的概念;确定了计算类别型数据的相似度;给出聚类结果清晰度及其变化率的定义;提出一种对质量和特征向量有效聚类类别型数据的算法.     

人力资本、从业特征与性别收入差异分析

基于中国家庭动态跟踪调查（CFPS）2010年数据,本文采用多元嵌套模型性别收入差异的影响因素。结果表明：中国劳动力市场上存在显著的性别收入差异、行业隔离和职业隔离。学历因素是对性别收入差异影响最大的个体特征,其次是职业和行业因素。     

就业极化、职业分割与流动人口性别工资差距

技术进步使我国流动人口分别流向工资较低的非常规操作型职业和工资较高的非常规认知型职业中，导致就业极化现象。女性向上述职业转移的趋势更为明显，这理论上会缩小性别工资差距，但现实中该差距却保持稳定。文章基于Brown分解法探讨了这一矛盾现象。实证结果表明：第一，流动人口转移到非常规职业后，降低了职业分割引致的就业性别歧视，提升了职业内部针对女性的工资歧视，因此性别工资差距保持稳定；第二，流动人口的职业转移缓解了非常规认知型、常规型职业针对女性的就业歧视；第三，劳动力流向非常规职业提升了其职业内工资歧视的解释力度，加剧了就业市场上的职业内工资歧视。     

大学生报考公务员动机的探索性研究

通过对574名报考公务员大学生的问卷调查研究表明：大学生在报考公务员时的动机依次为追求工作待遇、缓解就业压力、追求社会地位、追求社会期望、追求权利资源、实现政治抱负、实现素质与职位匹配,并就不同性别、生源地、学校层次对大学生的报考动机进行了比较分析。     

A Graphical Diagnostic for Identifying Influential Model Choices in Bayesian Hierarchical Models

Abstract. Real‐world phenomena are frequently modelled by Bayesian hierarchical models. The building‐blocks in such models are the distribution of each variable conditional on parent and/or neighbour variables in the graph. The specifications of centre and spread of these conditional distributions may be well motivated, whereas the tail specifications are often left to convenience. However, the posterior distribution of a parameter may depend strongly on such arbitrary tail specifications. This is not easily detected in complex models. In this article, we propose a graphical diagnostic, the Local critique plot, which detects such influential statistical modelling choices at the node level. It identifies the properties of the information coming from the parents and neighbours (the local prior) and from the children and co‐parents (the lifted likelihood) that are influential on the posterior distribution, and examines local conflict between these distinct information sources. The Local critique plot can be derived for all parameters in a chain graph model.     

城镇劳动力市场上的性别工资差异问题研究

经济转型以来，中国城镇劳动力市场上女性工资与男性工资存在很大差距。文章利用Brown分解方法对中国城镇职工的性别工资差距进行了分解。分解结果显示，职业内工资差异与职业间工资差异分别为19．8％和18．4％，即存在比较严重的纵向和横向性别职业隔离。此外，受教育程度、工作年限等人力资本水平对男女工资差异有显著的影响，职业性别歧视也是导致城镇劳动力市场上男女工资差异的主要原因。     

Umvu estimators for the population mean and variance based on random effects models for lognormal data

Cross-classified data are often obtained in controlled experimental situations and in epidemiologic studies. As an example of the latter, occupational health studies sometimes require personal exposure measurements on a random sample of workers from one or more job groups, in one or more plant locations, on several different sampling dates. Because the marginal distributions of exposure data from such studies are generally right-skewed and well-approximated as lognormal, researchers in this area often consider the use of ANOVA models after a logarithmic transformation. While it is then of interest to estimate original-scale population parameters (e.g., the overall mean and variance), standard candidates such as maximum likelihood estimators (MLEs) can be unstable and highly biased. Uniformly minimum variance unbiased (UMVU) cstiniators offer a viable alternative, and are adaptable to sampling schemes that are typiral of experimental or epidemiologic studies. In this paper, we provide UMVU estimators for the mean and variance under two random effects ANOVA models for logtransformed data. We illustrate substantial mean squared error gains relative to the MLE when estimating the mean under a one-way classification. We illustrate that the results can readily be extended to encompass a useful class of purely random effects models, provided that the study data are balanced.     

Methods for Quantitative Risk Assessment Using Occupational Studies

Although carcinogenic risk assessment is frequently based on animal bioassay data, occupational studies are generally considered the best source of data for quantitative risk estimation. The model selected for use with occupational study data is required to extrapolate on age, exposure level, and temporal exposure pattern. Relative and absolute risk models are examined, as are alternatives for the definition of a dose (exposure) variable. The models express disease incidence as a function of the chosen exposure variable and convert incidence into estimates of lifetime risk. In this form, predictions of the models can be compared. The methods are illustrated using three examples: arsenic exposure and respiratory cancer, leukemia associated with benzene exposure, and asbestos-induced mesothelioma.     

The Collection and Management of Occupational Exposure Data

This presentation addresses a number of issues pertinent to the collection and management of occupational exposure data and offers suggestions to those persons who are developing systems to handle large volumes of occupational exposure data. A perspective is taken that aims to meet the traditional objectives of industrial hygienists while accommodating epidemiologic needs for linking occupational exposure and health outcome data. The suggestions are based on experience gained through the retrospective use of industrial hygiene data in a large number of epidemiologic studies.